Improved image quality of low-dose CT combining with iterative model reconstruction algorithm for response assessment in patients after treatment of malignant tumor | Zendy

Xiaoyan Xin | Zendy; Jingtao Shen | Zendy; Shangwen Yang | Zendy; Song Liu | Zendy; Anning Hu | Zendy; Bin Zhu | Zendy; Yan Jiang | Zendy; Baoxin Li | Zendy; Bing Zhang | Zendy

Open Access

Improved image quality of low-dose CT combining with iterative model reconstruction algorithm for response assessment in patients after treatment of malignant tumor

Author(s) -

Xiaoyan Xin,

Jingtao Shen,

Shangwen Yang,

Song Liu,

Anning Hu,

Bin Zhu,

Yan Jiang,

Baoxin Li,

Bing Zhang

Publication year - 2018

Publication title -

quantitative imaging in medicine and surgery

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.766

H-Index - 21

eISSN - 2223-4292

pISSN - 2223-4306

DOI - 10.21037/qims.2018.08.05

Subject(s) - algorithm , computer science , image quality , computed tomography , quality (philosophy) , medicine , radiology , medical physics , artificial intelligence , image (mathematics) , philosophy , epistemology

To evaluate the image quality and radiation dose of low-dose (LD) computed tomography (LD-CT) combining with iterative model reconstruction (IMR) algorithm for response assessment in patients after treatment of malignant tumor compared with routine-dose CT (RD-CT).

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